Fei-Fei Cheng

1.8k citations
41 papers · 1.3k · h-index 18

Impact in

Papers in

Fei-Fei Cheng

38 papers receiving 1.3k citations

Peers

Fei-Fei Cheng
Comparison fields: 5 of 125
  • Information Systems and Management 395
  • Marketing 409
  • General Decision Sciences 52
  • Organizational Behavior and Human Resource Management 140
  • Management Information Systems 107
Replace Chin-Shan Wu with:
Chin-Shan Wu Taiwan
Gabriele Pizzi Italy
Glenn J. Browne United States
Markus Langer Germany
Dinesh K. Gauri United States
Mark Vandenbosch Canada
Paul R. Messinger Canada
Henner Gimpel Germany
Xiang Fang United States
Ajay K. Manrai United States
Fei-Fei Cheng relative to Chin-Shan Wu Taiwan Chin-Shan Wu's profile →
Citations per field
00.5×1.7×
Chin-Shan Wu · 1×
Citations per year

Countries citing papers authored by Fei-Fei Cheng

Since Specialization
Citations

This map shows the geographic impact of Fei-Fei Cheng's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Fei-Fei Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fei-Fei Cheng more than expected).

Fields of papers citing papers by Fei-Fei Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fei-Fei Cheng. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Fei-Fei Cheng. The network helps show where Fei-Fei Cheng may publish in the future.

Co-authors

The 25 scholars most cited alongside Fei-Fei Cheng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Fei-Fei Cheng Line = papers co-authored together Fei-Fei Cheng links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010250
2 2008137
3 2008108
4 2020106
5 2018105
6 201084
7 201867
8 201060
9 201142
10 202241
11 201838
12 200736
13 202331
14 201728
15 202125
16 201421
17 201220
18 202019
19 200615
20 201914

About Fei-Fei Cheng

Fei-Fei Cheng is a scholar working on Sociology and Political Science, Marketing, Information Systems and Management, Organizational Behavior and Human Resource Management and Management Information Systems, having authored 41 papers that have together received 1.3k indexed citations. Recurring topics across this work include Technology Adoption and User Behaviour (10 papers), Digital Marketing and Social Media (9 papers), Customer Service Quality and Loyalty (7 papers), Consumer Retail Behavior Studies (5 papers), Behavioral Health and Interventions (4 papers), Color perception and design (4 papers), Consumer Behavior in Brand Consumption and Identification (4 papers) and Knowledge Management and Sharing (3 papers). The work is most often cited by research in Information Systems and Management (395 citations), Marketing (409 citations), General Decision Sciences (52 citations), Organizational Behavior and Human Resource Management (140 citations) and Management Information Systems (107 citations). Fei-Fei Cheng has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Chin-Shan Wu, David C. Yen, Yuwen Huang, Xin Ma, Hongfang Lü, Gang Hu, Yi‐Chieh Chen, Xiaodong Jing, Tong Chen and Tong Chen. Their work appears in journals such as Computers in Human Behavior, Library Hi Tech, Behaviour and Information Technology, Computers and Electronics in Agriculture and Journal of the Association for Information Systems.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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